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Unsupervised Learning with Self-Organizing Spiking Neural Networks
TLDR
A hybridization of self-organized map properties with spiking neural networks that retain many of the features of SOMs is presented, and using the optimal choice of parameters, this approach produces improvements over state-of-art spiking Neural networks.
View on IEEE
BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python
TLDR
It is argued that this package facilitates the use of spiking networks for large-scale machine learning problems and some simple examples by using BindsNET in practice are shown.
View on PubMed
Lattice map spiking neural networks (LM-SNNs) for clustering and classifying image data
TLDR
Spiking neural networks with a lattice architecture are introduced in this work, combining several desirable properties of SNNs and self-organized maps, including a population-level confidence rating, and an n-gram inspired method.
View on Springer
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